[Python-Dev] Postponed annotations break inspection of dataclasses (original) (raw)

Ivan Levkivskyi levkivskyi at gmail.com
Thu Sep 27 12:05:57 EDT 2018

Do we have a b.p.o. issue about this? If no, then I would recommend to open one, so that we will not loose track of this.

-- Ivan

On Sat, 22 Sep 2018 at 16:32, David Hagen <david at drhagen.com> wrote:

The new postponed annotations have an unexpected interaction with dataclasses. Namely, you cannot get the type hints of any of the data classes methods.

For example, I have some code that inspects the type parameters of a class's _init_ method. (The real use case is to provide a default serializer for the class, but that is not important here.) _ _from dataclasses import dataclass_ _from typing import gettypehints_ _class Foo:_ _pass_ _@dataclass_ _class Bar:_ _foo: Foo_ _print(gettypehints(Bar._init_))_ _ In Python 3.6 and 3.7, this does what is expected; it prints {'foo':_ _<class '_main_.Foo'>, 'return': <class 'NoneType'>}. However, if in Python 3.7, I add from _future_ import annotations, then this fails with an error: _ _NameError: name 'Foo' is not defined_ _ I know why this is happening. The _init_ method is defined in the dataclasses module which does not have the Foo object in its environment, and the Foo annotation is being passed to dataclass and attached to _init_ as the string "Foo" rather than as the original object Foo, but gettypehints for the new annotations only does a name lookup in the module where _init_ is defined not where the annotation is defined. I know that the use of lambdas to implement PEP 563 was rejected for performance reasons. I could be wrong, but I think this was motivated by variable annotations because the lambda would have to be constructed each time the function body ran. I was wondering if I could motivate storing the annotations as lambdas in class bodies and function signatures, in which the environment is already being captured and is code that usually only runs once.

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